Combining MUSIC Spatial Sampling and Bootstrap to Estimate Closed Space DOA for Few Samples

Autor:	Sidi Mohammed Hadj Irid, Samir Kameche
Rok vydání:	2018
Předmět:	Array processing Sampling (statistics) General Medicine Closed space Algorithm Mathematics
Zdroj:	Algerian Journal of Signals and Systems. 3:125-132
ISSN:	2676-1548 2543-3792
DOI:	10.51485/ajss.v3i3.68
Popis:	DOA estimation in array processing uses MUSIC (Multiple Signal Classification) algorithm, mainly. It’s the most investigated technique and is very attractive because of its simplicity. However, it meets drawbacks and fails when only very few samples are available and the sources are very close or highly correlated. In these conditions, the problem is more intricate and the detection of targets becomes arduous. To overcome these problems, a new algorithm is developed in this paper. We combine bootstrap technique to increase sample size, spatial sampling and MUSIC method to improve resolution. Through different simulations, the performance and the effectiveness of the proposed approach, referred as spatial Sampling and Bootstrapped technique ‘’SSBoot’’, are demonstrated.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1928d8a3f214911a68abbbfef56bdd99 https://doi.org/10.51485/ajss.v3i3.68 Zobrazit plný text záznamu